Title :
Cluster partitioning in image analysis classification: a genetic algorithm approach
Author :
Alippi, Cesare ; Cucchiara, Rita
Author_Institution :
Dipartimento di Elettronica, Politecnico di Milano, Italy
Abstract :
A classification of data by using the genetic algorithm computational paradigm is proposed. The best data partition is defined to be the one minimizing the sum of Pythagorean distances between each datum in a cluster and the relative center of class or center of mass. Background is given, and the relevant genetic algorithm description is provided. The model for the genetic application is presented. Simulation results confirm genetic algorithms to be powerful tools for the solution of optimization problems.<>
Keywords :
genetic algorithms; image processing; Pythagorean distances; cluster partitioning; data partition; genetic algorithm computational paradigm; genetic algorithm description; genetic application; image analysis classification; optimization problems; relative center; Biological system modeling; Computer industry; Genetic algorithms; Image analysis; Image coding; Image processing; Image restoration; Image segmentation; Layout; Stochastic processes;
Conference_Titel :
CompEuro '92 . 'Computer Systems and Software Engineering',Proceedings.
Conference_Location :
The Hague, Netherlands
Print_ISBN :
0-8186-2760-3
DOI :
10.1109/CMPEUR.1992.218520
